Controlled natural language explained

Controlled natural languages (CNLs) are subsets of natural languages that are obtained by restricting the grammar and vocabulary in order to reduce or eliminate ambiguity and complexity. Traditionally, controlled languages fall into two major types: those that improve readability for human readers (e.g. non-native speakers),and those that enable reliable automatic semantic analysis of the language.[1] [2]

The first type of languages (often called "simplified" or "technical" languages), for example ASD Simplified Technical English, Caterpillar Technical English, IBM's Easy English, are used in the industry to increase the quality of technical documentation, and possibly simplify the semi-automatic translation of the documentation. These languages restrict the writer by general rules such as "Keep sentences short", "Avoid the use of pronouns", "Only use dictionary-approved words", and "Use only the active voice".[3]

The second type of languages have a formal syntax and formal semantics, and can be mapped to an existing formal language, such as first-order logic. Thus, those languages can be used as knowledge representation languages,[4] and writing of those languages is supported by fully automatic consistency and redundancy checks, query answering, etc.

Languages

Existing controlled natural languages include:[5] [6]

Encoding

IETF has reserved as a BCP 47 variant subtag for simplified versions of languages.[13]

See also

External links

Notes and References

  1. Web site: A Survey and Classification of Controlled Natural Languages . 2024-03-27 . direct.mit.edu.
  2. Web site: Controlled Natural Languages for language generation in artificial cognition . 2024-03-27 . IEEE.
  3. Controlling Controlled English – An Analysis of Several Controlled Language Rule Sets . Sharon . O'Brien . 2003 . Proceedings of EAMT-CLAW . 2011-12-30 . 2016-03-03 . https://web.archive.org/web/20160303181833/http://www.mt-archive.info/CLT-2003-Obrien.pdf . dead .
  4. Schwitter, Rolf. "Controlled natural languages for knowledge representation." Proceedings of the 23rd International Conference on Computational Linguistics: Posters. Association for Computational Linguistics, 2010.
  5. 10.1162/COLI_a_00168. A Survey and Classification of Controlled Natural Languages. 2014. Kuhn. Tobias. Computational Linguistics. 40. 121–170. 14586568. free. 1507.01701.
  6. Jonathan . Pool . Can Controlled Languages Scale to the Web? . 2006 . dead . https://web.archive.org/web/20090815035716/http://utilika.org/pubs/etc/ambigcl/clweb.html . 2009-08-15 .
  7. Norbert E. Fuchs . Kaarel Kaljurand . Gerold Schneider . Attempto Controlled English Meets the Challenges of Knowledge Representation, Reasoning, Interoperability and User Interfaces . FLAIRS 2006 . 2006 .
  8. Book: Ogden. Charles Kay. Basic English: A General Introduction with Rules and Grammar. 1930. Paul Treber & Co., Ltd.. London.
  9. Web site: Common Logic Controlled English. www.jfsowa.com. 27 August 2017.
  10. Kowalski, R., Dávila, J., Sartor, G. and Calejo, M., 2023. Logical English for law and education. In Prolog: The Next 50 Years (pp. 287-299). Cham: Springer Nature Switzerland.
  11. Wasik. Szymon. Prejzendanc. Tomasz. Blazewicz. Jacek. ModeLang: A New Approach for Experts-Friendly Viral Infections Modeling. Computational and Mathematical Methods in Medicine. 2013. 2013. 320715. 10.1155/2013/320715. 24454531. 3878415. free .
  12. Schwitter. Rolf. Tilbrook. M. PENG: Processable ENGlish. Technical Report, Macquarie University, Australia. 2004.
  13. Web site: Everson . Michael . Michael Everson . Registration form for 'simple' . IANA . 22 April 2021 . en.

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